1 citations · 3 across the 11 of their papers we have counts for
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ContactExplorer: Contact Coverage-Guided Exploration for General-Purpose Dexterous Manipulation
Zixuan Liu, Ruoyi Qiao, Chenrui Tie +5
Reinforcement learning explores effectively in domains such as Atari games, navigation, and locomotion, where novelty over states or dynamics is a sufficient signal. In contrast, d…
ManiLong-Shot: Interaction-Aware One-Shot Imitation Learning for Long-Horizon Manipulation
Zixuan Chen, Chongkai Gao, Lin Shao +3
One-shot imitation learning (OSIL) offers a promising way to teach robots new skills without large-scale data collection. However, current OSIL methods are primarily limited to sho…
DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Densely Cluttered Environments
Lixin Xu, Zixuan Liu, Zhewei Gui +6
Grasping objects in cluttered environments remains a fundamental yet challenging problem in robotic manipulation. While prior works have explored learning-based synergies between p…
MetaFold: Language-Guided Multi-Category Garment Folding Framework via Trajectory Generation and Foundation Model
Haonan Chen, Junxiao Li, Ruihai Wu +9
Garment folding is a common yet challenging task in robotic manipulation. The deformability of garments leads to a vast state space and complex dynamics, which complicates precise…
TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness
Jingxiang Guo, Jiayu Luo, Zhenyu Wei +5
Teleoperation provides an effective way to collect robot data, which is crucial for learning from demonstrations. In this field, teleoperation faces several key challenges: user-fr…
FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model
Chongkai Gao, Haozhuo Zhang, Zhixuan Xu +2
We aim to develop a model-based planning framework for world models that can be scaled with increasing model and data budgets for general-purpose manipulation tasks with only langu…
ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policy
Chenrui Tie, Yue Chen, Ruihai Wu +4
Imitation learning, e.g., diffusion policy, has been proven effective in various robotic manipulation tasks. However, extensive demonstrations are required for policy robustness an…
Grasp: A Unified Representation of Robot and Object Interaction for Cross-Embodiment Dexterous Grasping
Zhenyu Wei, Zhixuan Xu, Jingxiang Guo +5
Dexterous grasping is a fundamental yet challenging skill in robotic manipulation, requiring precise interaction between robotic hands and objects. In this paper, we present $\math…
ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robots
Zhixuan Xu, Chongkai Gao, Zixuan Liu +10
To substantially enhance robot intelligence, there is a pressing need to develop a large model that enables general-purpose robots to proficiently undertake a broad spectrum of man…
RiEMann: Near Real-Time SE(3)-Equivariant Robot Manipulation without Point Cloud Segmentation
Chongkai Gao, Zhengrong Xue, Shuying Deng +4
We present RiEMann, an end-to-end near Real-time SE(3)-Equivariant Robot Manipulation imitation learning framework from scene point cloud input. Compared to previous methods that r…